In R, extract rows based on strings in different columns - r

Question

Sorry if the solution to my problem is already out there, and I overlooked it. There are a lot of similar topics which all helped me understand the basics of what I'm trying to do, but did not quite solve my exact problem.
I have a data frame df:
> type = c("A","A","A","A","A","A","B","B","B","B","B","B")
> place = c("x","y","z","x","y","z","x","y","z","x","y","z")
> value = c(1:12)
>
> df=data.frame(type,place,value)
> df
type place value
1 A x 1
2 A y 2
3 A z 3
4 A x 4
5 A y 5
6 A z 6
7 B x 7
8 B y 8
9 B z 9
10 B x 10
11 B y 11
12 B z 12
>
(my real data has 3 different values in type and 10 in place, if that makes a difference)
I want to extract rows based on the strings in columns m and n.
E.g. I want to extract all rows that contain A in type and x and z in place, or all rows with A and B in type and y in place.
This works perfectly with subset, but I want to run my scripts on different combinations of extracted rows, and adjusting the subset command every time isn't very effective.
I thought of using a vector containing as elements what to get from type and place, respectively.
I tried:
v=c("A","x","z")
df.extract <- df[df$type&df$place %in% v]
but this returns an error.
I'm a total beginner with R and programming, so please bear with me.

Answer 1

You could try
df[df$type=='A' & df$place %in% c('x','y'),]
# type place value
#1 A x 1
#2 A y 2
#4 A x 4
#5 A y 5
For the second case
df[df$type %in% c('A', 'B') & df$place=='y',]
Update
Suppose, you have many columns and needs to subset the dataset based on values from many columns. For example.
set.seed(24)
df1 <- cbind(df, df[sample(1:nrow(df)),], df[sample(1:nrow(df)),])
colnames(df1) <- paste0(c('type', 'place', 'value'), rep(1:3, each=3))
row.names(df1) <- NULL
You can create a list of the values from the columns of interest
v1 <- setNames(list('A', 'x', c('A', 'B'),
'x', 'B', 'z'), paste0(c('type', 'place'), rep(1:3, each=2)))
and then use Reduce
df1[Reduce(`&`,Map(`%in%`, df1[names(v1)], v1)),]

Answer 2

you can make a function extract :
extract<-function(df,type,place){
df[df$type %in% type & df$place %in% place,]
}
that will work for the different subsets you want to do :
df.extract<-extract(df=df,type="A",place=c("x","y")) # or just extract(df,"A",c("x","y"))
> df.extract
type place value
1 A x 1
2 A y 2
4 A x 4
5 A y 5
df.extract<-extract(df=df,type=c("A","B"),place="y") # or just extract(df,c("A","B"),"y")
> df.extract
type place value
2 A y 2
5 A y 5
8 B y 8
11 B y 11